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Penerapan Algoritma K-Means Clustering Dalam Pengelompokkan Kepadatan Penduduk: Application of K-Means Clustering Algorithm in Population Density Grouping Delia, Fenita; Rasmita Ngemba, Hajra; Hendra, Syaiful; Syahrullah, Syahrullah; Trezandy Lapatta, Nouval
Technomedia Journal Vol 9 No 3 (2025): February
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/tmj.v9i3.2270

Abstract

Uneven population density will have a negative impact if not considered. One way to tackle this problem is with population equity management planning policies. This research focuses on clustering population density areas, which is the ratio between population and area in Central Sulawesi Province. This research clustering is applied with data mining techniques, namely K-Means Clustering. The research stages are data collection, data understanding, data processing, clustering, clustering review, dashboard analysis, and accuracy testing with the tableau application in providing visualization of population density in the region. Based on the results of the algorithm calculation, it produces three clusters, cluster 0 being low population density, cluster 1 being high population density, and cluster 2 being medium population density. Cluster formation is based on the visualization produced by the research dataset through Sum Of Square Error analysis, silhouette coefficient, and elbow method. Clustering is formed, followed by dashboard visualization with the tableau application. The clustering results, based on the SSE calculation, produce a value of 4324505738.747303, meaning the determination of the number of clusters with a significant difference with the calculation of the number of previous groupings. Then the results of the silhouette analysis provide the highest average silhouette value at the number of clusters, namely 3 with a value of 0.6144435666457168, and the elbow method gives the result that the elbow point is at point 3, meaning the optimum number of clusters with 3 clusters.
PELATIHAN PERLUASAN PEMASARAN PRODUK UNGGULAN DAERAH PADA KELOMPOK PERTERNAK PUYUH DESA BINANGGA MENGGUNAKAN E-COMMERCE Laila, Rahmah; Rasmita Ngemba, Hajra; Imam Abdullah , Ahmad; Salhudin, Salhudin; Jonathan Wongkar, Noel Marcell; Dwiyanto, Andika
JURNAL PENGABDIAN FARMASI DAN SAINS Vol. 2 No. 1 (2023): Oktober 2023
Publisher : Jurusan Farmasi FMIPA Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/jpsf.2023.v2.i1.16544

Abstract

Permintaan telur burung puyuh semakin hari semakin meningkat seiring dengan bertambahnya jumlah penduduk. Tetapi dari jumlah permintaan masyarakat akan telur burung puyuh tersebut belum didukung oleh pengetahuan dan kemampuan para peternak mengenai pengembangan usaha. Hal ini berakibat pada tidak maksimalnya perkembangan usaha ternak puyuh. Pemasaran juga masih dilakukan secara tradisional dan masih kalah saing dengan promosi produk dari provinsi lain. Tujuan dari kegiatan ini adalah memberikan pembinaan tentang bagaimana cara memanfaatkan teknologi untuk pemasaran penjualan telur puyuh yang efektif dan untuk pengembangan usaha dan cara pemasarannya. Adapun kegiatan sosialisasi yang dilakukan adalah dengan pemberian materi, pelatihan penggunaan aplikasi serta diskusi dengan mitra. Sosialisasi yang telah dilakukan sangat bermanfaat buat para peternak untuk mengembangkan pengetahuan dan skill peternak dalam melakukan penjualan dan merketing. Hal ini terbukti dengan ketercapaian hasil yang ditargetkan oleh tim pengabdi berupa pengaplikasian secara langsung penggunaan aplikasi dan peserta berhasil mendaftarkan akun mereka pada marketplace dengan baik.
Contract Staff Acceptance Selection Using Simple Additive Weighting (SAW) Method Kusumawati, Dewi; Grace , Diana; Rusydi, Muh; Rahmawaty; Rasmita Ngemba, Hajra; Hidayat, Nurul; Rahmawati, Siti
Tadulako Science and Technology Journal Vol. 1 No. 1 (2020): TADULAKO SCIENCE AND TECHNOLOGY JOURNAL
Publisher : LPPM Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/sciencetech.v1i1.15293

Abstract

Introduction : Technology is a supporter in making decisions made by a top-level leader. Good decision making will produce a good decision. An example of decision making is the determination of an honorary employment appointment at an agency. In some areas, there are still various offices or government agencies whose recruitment process has not been carried out professionally, but still in the usual ways in the environment such as friendship or family relations. This research designed a web-based decision support system application using SAW method to support the labor selection process at the Class II Agricultural Quarantine Center in Palu. The type of research conducted is qualitative descriptive study. The system development method used in this research is Waterfall development. Waterfall method is the workmanship of a system carried out sequentially or linearly. The analytical method used is Simple Additive Weighting (SAW). This method used because the basic concept of SAW method is to find a weighted sum of the performance ratings on each alternative of all attributes. The programming language used is PHP, while the database used is MySQL. The method used to test this system is black box testing method. Based on manual calculations as a comparison with the calculation of the system built, it can be obtained same results for its value. In addition, the results of ranking was obtained, where the alternative manual calculation that has the highest value is Fadila with a vector value of 1.00.